This project focuses on understanding how the brain constructs networks of interacting regions (i.e., neural networks) to perform cognitive tasks, especially those associated with audition and language, and how these networks are altered in brain disorders. These issues are addressed by combining computational neuroscience techniques with functional neuroimaging data, obtained using positron emission tomography (PET) or functional magnetic resonance imaging (fMRI) (reviewed in Horwitz and Braun, Brain and Language, 2004). The network analysis methods allow us to evaluate how brain operations differ between tasks, and between normal and patient populations. This research will allow us to ascertain which networks are dysfunctional, and the role neural plasticity plays in enabling compensatory behavior to occur. We have begun delineating the functional networks involved in the production of spontaneous narrative speech in normal subjects using PET measurements of regional cerebral blood flow (rCBF), an index of neural activity. We determined the functional connectivity (evaluated as the correlation between rCBF in different brain areas) of left hemisphere (LH) brain regions. Our results demonstrate that in normal subjects LH perisylvian regions interact strongly with one another during language production, but not during a task requiring similar muscle movements and vocalizations as speech. In patients who stutter, many of these strong functional linkages seem to be absent, suggesting that LH language-production networks are abnormal during stuttering (Horwitz and Braun, Brain and Language, in 2004). In another study, we demonstrated that differences in an individual?s strategy related to performing a task can be related to the effective connectivity between specific, task-related brain regions (Glabus et al., Cerebral Cortex, 2003). For language function, one important part of the left inferior frontal gyrus is Broca's area, which is defined as the cytoarchitectonic areas 44 and 45 in the system devised by Brodmann. We used a probabilistic data set corresponding to cytoarchitectonically-defined Brodmann areas (BA) 44 and 45, which enables us to say for any given voxel in the stereotactic space of the Talairach atlas, what the probability is that this voxel is in BA44 or BA45. We applied this probabilistic atlas to PET data acquired during language production tasks (generation of narrative speech) from adults whose parents were deaf and who were fluent in both speech and American Sign Language (ASL). Narrative production was performed in separate PET scans using speech and sign. We found similar activations of the central parts of both Brodmann areas by both speech and sign, suggesting that in spite of the different modalities by which speech and sign are expressed, the same neural substrates in Broca's region are engaged (Horwitz et al., Neuropsychologia, 2004). Another major focus of our laboratory seeks to understand the relationship between what is observed in functional neuroimaging studies and the underlying neural dynamics. To do this, we had previously constructed a large-scale computer model of neuronal dynamics that performs a visual object-matching task similar to those designed for PET/fMRI studies (for a review, see Horwitz, NeuroInformatics, 2004). In the last year, we have also expanded the model so that it can also simulate auditory processing, thus allowing us to investigate the neural basis of auditory object processing in the cerebral cortex. We developed a large-scale, neurobiologically realistic network model of auditory pattern recognition that relates neuronal dynamics of cortical auditory processing of frequency modulated (FM) sweeps to functional neuroimaging data obtained using PET and fMRI. Areas included in the model extend from primary auditory to prefrontal cortex. The electrical activities of the neuronal units of model were constrained to agree with data from the neurophysiological literature regarding the perception of FM sweeps. We also conducted an fMRI experiment using stimuli and tasks similar to those used in our simulations. The integrated synaptic activity of the neuronal units of the model was used to determine simulated hemodynamic measures, and generally agreed with the experimentally observed fMRI data in the brain regions corresponding to the modules of the model. Our results demonstrate that the model is capable of exhibiting the salient features of both electrophysiological neuronal activities and fMRI values that are in agreement with empirically observed data. These findings provide support for our hypotheses concerning how auditory objects are processed by primate neocortex (Husain et al., NeuroImage, 2004). Environmentally relevant auditory stimuli are often composed of long-duration tonal patterns (e.g., multisyllabic words, short sentences, melodies). Manipulation of those patterns by the brain requires working memory to temporarily store the segments of the pattern and integrate them into a percept. To understand the neural basis of how this is accomplished, we extended the model of auditory recognition of short-duration tonal patterns described above. A memory buffer and a gating module were added. The memory buffer increased the storage capacity of PFC; the gating module distributed the segments of the input pattern to separate locations of the memory buffer in an orderly fashion, allowing a subsequent comparison of the stored segments against the segments of a second pattern. Current simulations show that the extended model performs match and mismatch of sequences of long-duration tonal patterns in a DMS task. Our model can also simulate fMRI data by representing the fMRI signal in each module as proportional to the time-integrated synaptic activity. We conducted an fMRI experiment using the same stimuli as employed in the simulations and found areas in the prefrontal cortex that are likely candidate brain areas for the new modules of the extended model. Based on single-cell and fMRI data, two different current models of the topographical and functional organization of the prefrontal cortex have been proposed: an organization-by-stimulus-domain model and an organization-by-process model. We used a computational neuroscience-based approach to integrate, via a detailed large-scale microscopic neurodynamical computational model, single-cell and fMRI measurements of the prefrontal cortex (PFC) associated with working memory processing in order to investigate this issue. For this purpose, we formulated an explicit model of the spiking and synaptic dynamical mechanisms underlying working memory-related activity during the execution of delay tasks with a ?what ??then ??where ?design (object and spatial delayed response within the same trial). It was shown that the f MRI data characteristic of the dorsal PFC and linked to spatial processing and manipulation of items can be reproduced in the model by a high level of inhibition, whereas the f MRI data characteristic of the ventral PFC and linked to object processing can be produced by a lower level of inhibition, even though the network is itself topographically homogeneous with no spatial topology of the neurons (Deco et al., J. Cogn. Neurosci., 2004).